Princeton Satellite Systems (United States)

Risk-Based Software Test Prioritization via Machine-Learning Defect Prediction: Label-Feature Circularity, Clean Baselines, and an Honest Empirical Study on Five Open-Source Repositories

Risk-based software testing seeks to allocate CI test-execution effort proportional to estimated defect likelihood, typically via a machine-learning classifier trained on repository process metrics. We show that the standard formulation harbours a fatal label-feature circularity:...

Risk-Based Software Test Prioritization via Machine-Learning Defect Prediction: Label-Feature Circularity, Clean Baselines, and an Honest Empirical Study on Five Open-Source Repositories

Risk-based software testing seeks to allocate CI test-execution effort proportional to estimated defect likelihood, typically via a machine-learning classifier trained on repository process metrics. We show that the standard formulation harbours a fatal label-feature circularity:...